1. Field of the Invention
The present invention relates to a system and method for analyzing samples, such as biological samples, to determine the susceptibility of the samples to antimicrobial materials, such as antibiotics. More particularly, the present invention relates to a system and method which takes a plurality of optical readings of a biological sample contained in sample wells of a sample test panel having various types and concentrations of antimicrobial materials therein and, based on these readings, determines the respective minimum inhibitory concentrations (MICs) at which the respective antimicrobial materials will inhibit growth of the sample.
2. Description of the Related Art
Many conventional systems exist for performing tests on microbiological samples related to patient diagnosis and therapy. The microbiological samples may come from a variety of sources, including infected wounds, genital infections, cerebro-spinal fluids, blood, abscesses or any other suitable source. From the microorganism samples, an inoculum is prepared in accordance with established procedures which produce a bacterial or cellular suspension of a predetermined concentration. Further processing of the suspension may depend on the testing method employed, as can be appreciated by one skilled in the art.
The conventional systems are used, for example, to identify the types of microorganisms present in a patient's sample. Typically, in such systems, reagents are placed into cupules, or test wells, of identification trays, into which the sample is introduced. The reagents change color in the presence of an actively growing culture of microorganisms. Based on the color change, or lack thereof, the microorganism can be identified by the use of reference tables.
Other systems have been developed for susceptibility testing of microorganisms. These systems are used to determine the susceptibility of a microorganism in a sample to various therapeutics, such as antibiotics. Based on these test results, physicians can then, for example, prescribe an antimicrobial product which will be successful in eliminating or inhibiting growth of the microorganism. Qualitative susceptibility testing, in particular, provides an indication of whether a microorganism is resistant or sensitive to a particular antibiotic, but does not provide an indication on the degree of sensitivity or resistance of the microorganism. On the other hand, quantitative susceptibility testing provides an indication of the concentration of the antimicrobial agent needed to inhibit growth of the microorganism. The term minimum inhibitory concentration (MIC) is used to refer to the minimum concentration of the antimicrobial agent that is required to inhibit the growth of a microorganism.
Although the conventional systems can be somewhat useful in determining the MICs at which respective antimicrobial agents will inhibit growth of respective microorganisms, these systems have certain drawbacks. For example, when performing identification and susceptibility testing, the test trays are incubated at a controlled temperature for an extended period of time. At predetermined time intervals, the wells of the test trays are individually examined for an indication of color change or other test criteria. However, this process can be long and tedious when performed manually by a technician. In addition, the incubation times for identification and susceptibility test trays may differ, or the optimal time to read a test result from the test tray may not be known in advance. Thus, a technician may typically need to read and record results for a specimen at several different times, sometimes far apart, which may cause assignment or correlation errors.
Automated systems are desirable in performing these tests to minimize the technician handling time, as well as to minimize the possibility of human error. In addition, automated systems may be preferred because they generally can obtain results more rapidly and accurately than manual methods. One known microbiological testing apparatus for the automatic incubation and reading of microbiological samples employs a plurality of test trays having a plurality of wells which contain the samples or agents to be tested. The trays are first placed in an incubator, and are then moved to an inspection station after a sufficient incubation period. A light source is disposed above the tray and a pair of video cameras are disposed below the tray at the inspection station. Each video camera takes a video image of an entire tray, and the video image signal of the entire tray is sent to an image processor to be analyzed.
The image processor requires uniform lighting over the entire inspection station. Consequently, the processor records the background light level of each pixel within an area of interest corresponding to each well of the tray to account for variability in the light source. The image processor processes the video image of the tray and determines the number of pixels for a particular well whose intensity exceeds a predetermined threshold for that area of interest. If the number of pixels exceeds a predetermined number, a positive result is assigned to that well. The image processor analyzes the binary partial results from the wells to determine the possible identity of the microorganisms. The binary partial results are compared to prerecorded patterns of results for each type of test tray to identify the sample in question.
A microbiological testing apparatus for detecting the presence of a fluorescence emitting reaction resulting from the interaction of a reacting agent and a sample for detection, susceptibility, and identification testing, is also known. In this apparatus, multiple trays having a plurality of test chambers are contained within a carousel. This carousel is rotated to move one of the trays close to a detection area. A positioning mechanism then radially moves that tray out of the carousel and into the detection area, and a high-energy light source is disposed proximate to the tray. The light source provides narrow-band light sufficient to produce an emission fluorescence from the reaction within the test chambers, which in turn is detected by a video mechanism disposed opposite to the light source and behind the positioned tray. The video mechanism produces an image based on the emission wavelength.
Another test system is known for identifying bacteria using signals based on the intensity of monochromatic light reflected from specimens placed in a culture plate having a plurality of cells. A rotary disk containing six interference filters is interposed between a lamp and a group of optical fibers. The light from the lamp passes through a particular interference filter to produce monochromatic light of a certain wavelength. The filtered monochromatic light is guided by the optical fibers to be incident on respective cells of the culture plate. The disk is rotated so that the six different wavelength monochromatic lights are caused to be incident on the cells sequentially. The light reflected from the specimens is guided by additional optical fibers to corresponding phototransistors. A signal is derived for each specimen based on the intensity of the reflected monochromatic light. These signals are then analyzed to determine the identity of the specimen by calculating the difference, or ratio, between the signals and comparing that result with a reference value.
Although the above-described systems may be somewhat useful, each system fails to fulfill all of the requirements of a fully automated microbiological testing system. In particular, the known systems are not capable of simultaneously performing both colorimetric-type and fluorometric-type testing on multiple-well test panels, which is needed to obtain more accurate test results. Further, these systems are generally not designed to continuously gather test data from a plurality of multiple-well test panels in a quick and reliable manner. Moreover, the automated processing of these systems is limited.
In addition, the known systems do not examine multiple indicators of growth of the samples, and then base the MIC calculations on these multiple growth indicators. The use of data from multiple growth indicators is desirable to provide increased accuracy and integrity of the results. Furthermore, the known systems fail to employ a method of screening questionable MIC results. In particular, the known systems do not evaluate the quality and reliability of the MIC results to provide a probability or confidence value which indicates the level of certainty at which the MIC results are deemed to be correct.
Accordingly, a need exists for a system and method for an improved system and method for analyzing biological samples to determine the susceptibility of the samples to antimicrobial materials, and to provide MIC values for the antimicrobial materials with respect to the various samples.